Estimation of the All-Wave All-Sky Land Surface Daily Net Radiation at Mid-Low Latitudes from MODIS Data Based on ERA5 Constraints

The surface all-wave net radiation (Rn) plays an important role in the energy and water cycles, and most studies of Rn estimations have been conducted using satellite data. As one of the most commonly used satellite data sets, Moderate Resolution Imaging Spectroradiometer (MODIS) data have not been widely used for radiation calculations at mid-low latitudes because of its very low revisit frequency. To improve the daily Rn estimation at mid-low latitudes with MODIS data, four models, including three models built with random forest (RF) and different temporal expansion models and one model built with the look-up-table (LUT) method, are used based on comprehensive in situ radiation measurements collected from 340 globally distributed sites, MODIS top-of-atmosphere (TOA) data, and the fifth generation of European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5) data from 2000 to 2017. After validation against the in situ measurements, it was found that the RF model based on the constraint of the daily Rn from ERA5 (an RF-based model with ERA5) performed the best among the four proposed models, with an overall validated root-mean-square error (RMSE) of 21.83 Wm−2, R2 of 0.89, and a bias of 0.2 Wm−2. It also had the best accuracy compared to four existing products (Global LAnd Surface Satellite Data (GLASS), Clouds and the Earth’s Radiant Energy System Edition 4A (CERES4A), ERA5, and FLUXCOM_RS) across various land cover types and different elevation zones. Further analyses illustrated the effectiveness of the model by introducing the daily Rn from ERA5 into a “black box” RF-based model for Rn estimation at the daily scale, which is used as a physical constraint when the available satellite observations are too limited to provide sufficient information (i.e., when the overpass time is less than twice per day) or the sky is overcast. Overall, the newly-proposed RF-based model with ERA5 in this study shows satisfactory performance and has strong potential to be used for long-term accurate daily Rn global mapping at finer spatial resolutions (e.g., 1 km) at mid-low latitudes.

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Exploring the Potential of Satellite Solar-Induced Fluorescence to Constrain Global Transpiration Estimates

Remote Sensing ◽

10.3390/rs11040413 ◽

2019 ◽

Vol 11 (4) ◽

pp. 413 ◽

Cited By ~ 10

Author(s):

Brianna Pagán ◽

Wouter Maes ◽

Pierre Gentine ◽

Brecht Martens ◽

Diego Miralles

Keyword(s):

Eddy Covariance ◽

Land Surface ◽

Radiant Energy ◽

Energy System ◽

Plant Responses ◽

Natural Ecosystem ◽

Growing Seasons ◽

Phenological Changes ◽

Opening And Closing

The opening and closing of plant stomata regulates the global water, carbon and energy cycles. Biophysical feedbacks on climate are highly dependent on transpiration, which is mediated by vegetation phenology and plant responses to stress conditions. Here, we explore the potential of satellite observations of solar-induced chlorophyll fluorescence (SIF)—normalized by photosynthetically-active radiation (PAR)—to diagnose the ratio of transpiration to potential evaporation (‘transpiration efficiency’, τ). This potential is validated at 25 eddy-covariance sites from seven biomes worldwide. The skill of the state-of-the-art land surface models (LSMs) from the eartH2Observe project to estimate τ is also contrasted against eddy-covariance data. Despite its relatively coarse (0.5°) resolution, SIF/PAR estimates, based on data from the Global Ozone Monitoring Experiment 2 (GOME-2) and the Clouds and Earth’s Radiant Energy System (CERES), correlate to the in situ τ significantly (average inter-site correlation of 0.59), with higher correlations during growing seasons (0.64) compared to decaying periods (0.53). In addition, the skill to diagnose the variability of in situ τ demonstrated by all LSMs is on average lower, indicating the potential of SIF data to constrain the formulations of transpiration in global models via, e.g., data assimilation. Overall, SIF/PAR estimates successfully capture the effect of phenological changes and environmental stress on natural ecosystem transpiration, adequately reflecting the timing of this variability without complex parameterizations.

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QUANTIFYING THE CONTRIBUTIONS OF ENVIRONMENTAL PARAMETERS TO CERES SURFACE NET RADIATION ERROR IN CHINA

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-3-1339-2018 ◽

2018 ◽

Vol XLII-3 ◽

pp. 1339-1345

Author(s):

X. Pan ◽

Y. Yang ◽

Y. Liu ◽

X. Fan ◽

L. Shan ◽

...

Keyword(s):

Land Surface ◽

Southern China ◽

Radiant Energy ◽

Environmental Parameters ◽

High Sensitivity ◽

Precipitable Water ◽

Energy System ◽

Net Radiation ◽

Error Source ◽

Error Sources

Error source analyses are critical for the satellite-retrieved surface net radiation (Rn) products. In this study, we evaluate the Rn error sources in the Clouds and the Earth’s Radiant Energy System (CERES) project at 43 sites from July in 2007 to December in 2007 in China. The results show that cloud fraction (CF), land surface temperature (LST), atmospheric temperature (AT) and algorithm error dominate the Rn error, with error contributions of ~-20, ~15, ~10 and ~10&thinsp;W/m2 (net shortwave (NSW)/longwave (NLW) radiation), respectively. For NSW, the dominant error source is algorithm error (more than 10&thinsp;W/m2), particularly in spring and summer with abundant cloud. For NLW, due to the high sensitivity of algorithm and large LST/CF error, LST and CF are the largest error sources, especially in northern China. The AT influences the NLW error large in southern China because of the large AT error in there. The total precipitable water has weak influence on Rn error even with the high sensitivity of algorithm. In order to improve Rn quality, CF and LST (AT) error in northern (southern) China should be decreased.

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Plot-scale retrieval of land surface temperature and emissivity estimation

10.5194/egusphere-egu21-3962 ◽

2021 ◽

Author(s):

Gitanjali Thakur ◽

Stan Schymanski ◽

Kaniska Mallick ◽

Ivonne Trebs

Keyword(s):

Land Cover ◽

Surface Temperature ◽

Land Surface Temperature ◽

Satellite Data ◽

Land Surface ◽

Longwave Radiation ◽

Landscape Scale ◽

The Earth ◽

Downwelling Longwave Radiation

The surface energy balance (SEB) is defined as the balance between incoming energy from the sun and outgoing energy from the Earth&#8217;s surface. All components of the SEB depend on land surface temperature (LST). Therefore, LST is an important state variable that controls the energy and water exchange between the Earth&#8217;s surface and the atmosphere. LST can be estimated radiometrically, based on the infrared radiance emanating from the surface. At the landscape scale, LST is derived from thermal radiation measured using&#160; satellites.&#160; At the plot scale, eddy covariance flux towers commonly record downwelling and upwelling longwave radiation, which can be inverted to retrieve LST&#160; using the grey body equation : &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; Rlup = &#949;&#963; Ts4 + (1 &#8722; &#949;) R ldw&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; (1) where Rlup is the upwelling longwave radiation, Rldw is the downwelling longwave radiation, &#949; is the surface emissivity, Ts&#160; is the surface temperature and &#963;&#160; is the Stefan-Boltzmann constant. The first term is the temperature-dependent part, while the second represents reflected longwave radiation. Since in the past downwelling longwave radiation was not measured routinely using flux towers, it is an established practice to only use upwelling longwave radiation for the retrieval of plot-scale LST, essentially neglecting the reflected part and shortening Eq. 1 to: &#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160;&#160; Rlup = &#949;&#963; Ts4 &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160; &#160;&#160; (2) Despite&#160; widespread availability of downwelling longwave radiation measurements, it is still common to use the short equation (Eq. 2) for in-situ LST retrieval. This prompts the question if ignoring the downwelling longwave radiation introduces a bias in LST estimations from tower measurements. Another associated question is how to obtain the correct &#949; needed for in-situ LST retrievals using tower-based measurements. The current work addresses these two important science questions using observed fluxes at eddy covariance towers for different land cover types. Additionally, uncertainty in retrieved LST and emissivity due to uncertainty in input fluxes was quantified using SOBOL-based uncertainty analysis (SALib). Using landscape-scale emissivity obtained from satellite data (MODIS), we found that the LST&#160; obtained using the complete equation (Eq. 1) is 0.5 to 1.5 K lower than the short equation (Eq. 2). Also, plot-scale emissivity was estimated using observed sensible heat flux and surface-air temperature differences. Plot-scale emissivity obtained using the complete equation was generally between 0.8 to 0.98 while the short equation gave values between 0.9 to 0.98, for all land cover types. Despite additional input data for the complete equation, the uncertainty in plot-scale LST was not greater than if the short equation was used. Landscape-scale daytime LST obtained from satellite data (MODIS TERRA) were strongly correlated with our plot-scale estimates, but on average higher by 0.5 to 9 K, regardless of the equation used. However, for most sites, the correspondence between MODIS TERRA LST and retrieved plot-scale LST estimates increased significantly if plot-scale emissivity was used instead of the landscape-scale emissivity obtained from satellite data.

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A statistics-based temporal filter algorithm to map spatiotemporally continuous shortwave albedo from MODIS data

Hydrology and Earth System Sciences ◽

10.5194/hess-17-2121-2013 ◽

2013 ◽

Vol 17 (6) ◽

pp. 2121-2129 ◽

Cited By ~ 50

Author(s):

N. F. Liu ◽

Q. Liu ◽

L. Z. Wang ◽

S. L. Liang ◽

J. G. Wen ◽

...

Keyword(s):

Time Series ◽

Temporal Resolution ◽

Land Surface ◽

Surface Albedo ◽

Critical Role ◽

Radiant Energy ◽

High Temporal Resolution ◽

Land Surface Parameter ◽

Temporal Filter ◽

Moderate Resolution Imaging Spectroradiometer

Abstract. Land-surface albedo plays a critical role in the earth's radiant energy budget studies. Satellite remote sensing provides an effective approach to acquire regional and global albedo observations. Owing to cloud coverage, seasonal snow and sensor malfunctions, spatiotemporally continuous albedo datasets are often inaccessible. The Global LAnd Surface Satellite (GLASS) project aims at providing a suite of key land surface parameter datasets with high temporal resolution and high accuracy for a global change study. The GLASS preliminary albedo datasets are global daily land-surface albedo generated by an angular bin algorithm (Qu et al., 2013). Like other products, the GLASS preliminary albedo datasets are affected by large areas of missing data; beside, sharp fluctuations exist in the time series of the GLASS preliminary albedo due to data noise and algorithm uncertainties. Based on the Bayesian theory, a statistics-based temporal filter (STF) algorithm is proposed in this paper to fill data gaps, smooth albedo time series, and generate the GLASS final albedo product. The results of the STF algorithm are smooth and gapless albedo time series, with uncertainty estimations. The performance of the STF method was tested on one tile (H25V05) and three ground stations. Results show that the STF method has greatly improved the integrity and smoothness of the GLASS final albedo product. Seasonal trends in albedo are well depicted by the GLASS final albedo product. Compared with MODerate resolution Imaging Spectroradiometer (MODIS) product, the GLASS final albedo product has a higher temporal resolution and more competence in capturing the surface albedo variations. It is recommended that the quality flag should be always checked before using the GLASS final albedo product.

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Global maps of aerosol single scattering albedo using combined CERES-MODIS retrieval

10.5194/acp-2021-521 ◽

2021 ◽

Author(s):

Archana Devi ◽

Sreedharan Krishnakumari Satheesh

Keyword(s):

Climate Models ◽

Radiant Energy ◽

Energy System ◽

Single Scattering ◽

Global Scale ◽

Single Scattering Albedo ◽

Accurate Information ◽

Climatic Impact ◽

Aerosol Absorption ◽

Moderate Resolution Imaging Spectroradiometer

Abstract. Single Scattering Albedo (SSA) is a leading contributor to the uncertainty in aerosol radiative impact assessments. Therefore accurate information on aerosol absorption is required on a global scale. In this study, we have applied a multi-satellite algorithm to retrieve SSA using the concept of ‘critical optical depth.’ Global maps of SSA were generated following this approach using spatially and temporally collocated data from Clouds and the Earth’s Radiant Energy System (CERES) and Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on board Terra and Aqua satellites. The method has been validated using the data from aircraft-based measurements of various field campaigns. The retrieval uncertainty is ±0.03 and depends on both the surface albedo and aerosol absorption. Global mean SSA estimated over land and ocean is 0.93 and 0.97, respectively. Seasonal and spatial distribution of SSA over various regions are also presented. The global maps of SSA, thus derived with improved accuracy, provide important input to climate models for assessing the climatic impact of aerosols on regional and global scales.

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Evaluation of Five Satellite Top-of-Atmosphere Albedo Products over Land

Remote Sensing ◽

10.3390/rs11242919 ◽

2019 ◽

Vol 11 (24) ◽

pp. 2919

Author(s):

Chuan Zhan ◽

Richard P. Allan ◽

Shunlin Liang ◽

Dongdong Wang ◽

Zhen Song

Keyword(s):

High Latitude ◽

Radiant Energy ◽

Energy System ◽

Moderate Resolution ◽

Resolution Imaging ◽

Moderate Resolution Imaging Spectroradiometer ◽

Regional Product ◽

Changes Over Time ◽

Year 2000 ◽

Energy Pathways

Five satellite top-of-atmosphere (TOA) albedo products over land were evaluated in this study including global products from the Advanced Very High Resolution Radiometer (AVHRR) (TAL-AVHRR), Moderate Resolution Imaging Spectroradiometer (MODIS) (TAL-MODIS), and Clouds and the Earth’s Radiant Energy System (CERES); one regional product from the Climate Monitoring Satellite Application Facility (CM SAF); and one harmonized product termed Diagnosing Earth’s Energy Pathways in the Climate system (DEEP-C). Results showed that overall, there is good consistency among these five products, particularly after the year 2000. The differences among these products in the high-latitude regions were relatively larger. The percentage differences among TAL-AVHRR, TAL-MODIS, and CERES were generally less than 20%, while the differences between TAL-AVHRR and DEEP-C before 2000 were much larger. Except for the obvious decrease in the differences after 2000, the differences did not show significant changes over time, but varied among different regions. The differences between TAL-AVHRR and the other products were relatively large in the high-latitude regions of North America, Asia, and the Maritime Continent, while the differences between DEEP-C and CM SAF in Europe and Africa were smaller. Interannual variability was consistent between products after 2000, before which the differences among the three products were much larger.

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Angular Distribution Models for Top-of-Atmosphere Radiative Flux Estimation from the Clouds and the Earth’s Radiant Energy System Instrument on the Terra Satellite. Part I: Methodology

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech1712.1 ◽

2005 ◽

Vol 22 (4) ◽

pp. 338-351 ◽

Cited By ~ 207

Author(s):

Norman G. Loeb ◽

Seiji Kato ◽

Konstantin Loukachine ◽

Natividad Manalo-Smith

Keyword(s):

Angular Distribution ◽

Radiant Energy ◽

Tropical Rainfall Measuring Mission ◽

Energy System ◽

Distribution Models ◽

Radiative Fluxes ◽

Earth Observing System ◽

Moderate Resolution ◽

Moderate Resolution Imaging Spectroradiometer ◽

Terra Satellite

Abstract The Clouds and Earth’s Radiant Energy System (CERES) provides coincident global cloud and aerosol properties together with reflected solar, emitted terrestrial longwave, and infrared window radiative fluxes. These data are needed to improve the understanding and modeling of the interaction between clouds, aerosols, and radiation at the top of the atmosphere, surface, and within the atmosphere. This paper describes the approach used to estimate top-of-atmosphere (TOA) radiative fluxes from instantaneous CERES radiance measurements on the Terra satellite. A key component involves the development of empirical angular distribution models (ADMs) that account for the angular dependence of the earth’s radiation field at the TOA. The CERES Terra ADMs are developed using 24 months of CERES radiances, coincident cloud and aerosol retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS), and meteorological parameters from the Global Modeling and Assimilation Office (GMAO)’s Goddard Earth Observing System (GEOS) Data Assimilation System (DAS) V4.0.3 product. Scene information for the ADMs is from MODIS retrievals and GEOS DAS V4.0.3 properties over the ocean, land, desert, and snow for both clear and cloudy conditions. Because the CERES Terra ADMs are global, and far more CERES data are available on Terra than were available from CERES on the Tropical Rainfall Measuring Mission (TRMM), the methodology used to define CERES Terra ADMs is different in many respects from that used to develop CERES TRMM ADMs, particularly over snow/sea ice, under cloudy conditions, and for clear scenes over land and desert.

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Top-of-Atmosphere Direct Radiative Effect of Aerosols over Global Oceans from Merged CERES and MODIS Observations

Journal of Climate ◽

10.1175/jcli3504.1 ◽

2005 ◽

Vol 18 (17) ◽

pp. 3506-3526 ◽

Cited By ~ 139

Author(s):

Norman G. Loeb ◽

Natividad Manalo-Smith

Keyword(s):

Information Service ◽

Radiant Energy ◽

Energy System ◽

Surface Fluxes ◽

Radiative Effect ◽

Distribution Models ◽

Radiative Fluxes ◽

Clear Sky ◽

Moderate Resolution Imaging Spectroradiometer ◽

Global Oceans

Abstract The direct radiative effect of aerosols (DREA) is defined as the difference between radiative fluxes in the absence and presence of aerosols. In this study, the direct radiative effect of aerosols is estimated for 46 months (March 2000–December 2003) of merged Clouds and the Earth’s Radiant Energy System (CERES) and Moderate Resolution Imaging Spectroradiometer (MODIS) Terra global measurements over ocean. This analysis includes the contribution from clear regions in both clear and partly cloudy CERES footprints. MODIS–CERES narrow-to-broadband regressions are developed to convert clear-sky MODIS narrowband radiances to broadband shortwave (SW) radiances, and CERES clear-sky angular distribution models (ADMs) are used to estimate the corresponding top-of-atmosphere (TOA) radiative fluxes that are needed to determine the DREA. Clear-sky MODIS pixels are identified using two independent cloud masks: (i) the NOAA/National Environmental Satellite, Data, and Information Service (NESDIS) algorithm that is used for inferring aerosol properties from MODIS on the CERES Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product (NOAA SSF); and (ii) the standard algorithm that is used by the MODIS aerosol group to produce the MODIS aerosol product (MOD04). Over global oceans, direct radiative cooling by aerosols for clear scenes that are identified from MOD04 is estimated to be 40% larger than for clear scenes from NOAA SSF (5.5 compared to 3.8 W m−2). Regionally, differences are largest in areas that are affected by dust aerosol, such as oceanic regions that are adjacent to the Sahara and Saudi Arabian deserts, and in northern Pacific Ocean regions that are influenced by dust transported from Asia. The net total-sky (clear and cloudy) DREA is negative (cooling) and is estimated to be −2.0 W m−2 from MOD04, and −1.6 W m−2 from NOAA SSF. The DREA is shown to have pronounced seasonal cycles in the Northern Hemisphere and large year-to-year fluctuations near deserts. However, no systematic trend in deseasonalized anomalies of the DREA is observed over the 46-month time series that is considered.

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Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) Top-of-Atmosphere (TOA) Edition-4.0 Data Product

Journal of Climate ◽

10.1175/jcli-d-17-0208.1 ◽

2018 ◽

Vol 31 (2) ◽

pp. 895-918 ◽

Cited By ~ 176

Author(s):

Norman G. Loeb ◽

David R. Doelling ◽

Hailan Wang ◽

Wenying Su ◽

Cathy Nguyen ◽

...

Keyword(s):

Regional Differences ◽

Radiant Energy ◽

Energy System ◽

Polar Regions ◽

Marine Stratocumulus ◽

Clear Sky ◽

Data Product ◽

Cloud Radiative Effect ◽

Global Mean

The Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) top-of-atmosphere (TOA), Edition 4.0 (Ed4.0), data product is described. EBAF Ed4.0 is an update to EBAF Ed2.8, incorporating all of the Ed4.0 suite of CERES data product algorithm improvements and consistent input datasets throughout the record. A one-time adjustment to shortwave (SW) and longwave (LW) TOA fluxes is made to ensure that global mean net TOA flux for July 2005–June 2015 is consistent with the in situ value of 0.71 W m−2. While global mean all-sky TOA flux differences between Ed4.0 and Ed2.8 are within 0.5 W m−2, appreciable SW regional differences occur over marine stratocumulus and snow/sea ice regions. Marked regional differences in SW clear-sky TOA flux occur in polar regions and dust areas over ocean. Clear-sky LW TOA fluxes in EBAF Ed4.0 exceed Ed2.8 in regions of persistent high cloud cover. Owing to substantial differences in global mean clear-sky TOA fluxes, the net cloud radiative effect in EBAF Ed4.0 is −18 W m−2 compared to −21 W m−2 in EBAF Ed2.8. The overall uncertainty in 1° × 1° latitude–longitude regional monthly all-sky TOA flux is estimated to be 3 W m−2 [one standard deviation (1 σ)] for the Terra-only period and 2.5 W m−2 for the Terra– Aqua period both for SW and LW fluxes. The SW clear-sky regional monthly flux uncertainty is estimated to be 6 W m−2 for the Terra-only period and 5 W m−2 for the Terra– Aqua period. The LW clear-sky regional monthly flux uncertainty is 5 W m−2 for Terra only and 4.5 W m−2 for Terra– Aqua.

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Bias-correcting carbon fluxes derived from land-surface satellite data for retrospective and near-real-time assimilation systems

Atmospheric Chemistry and Physics ◽

10.5194/acp-21-9609-2021 ◽

2021 ◽

Vol 21 (12) ◽

pp. 9609-9628

Author(s):

Brad Weir ◽

Lesley E. Ott ◽

George J. Collatz ◽

Stephan R. Kawa ◽

Benjamin Poulter ◽

...

Keyword(s):

Remote Sensing ◽

Satellite Data ◽

Growth Rates ◽

Land Surface ◽

Surface Fluxes ◽

Short Latency ◽

Satellite Observations ◽

Seasonal Forecasts ◽

Spatial Coverage

Abstract. The ability to monitor and understand natural and anthropogenic variability in atmospheric carbon dioxide (CO2) is a growing need of many stakeholders across the world. Systems that assimilate satellite observations, given their short latency and dense spatial coverage, into high-resolution global models are valuable, if not essential, tools for addressing this need. A notable drawback of modern assimilation systems is the long latency of many vital input datasets; for example, inventories, in situ measurements, and reprocessed remote-sensing data can trail the current date by months to years. This paper describes techniques for bias-correcting surface fluxes derived from satellite observations of the Earth's surface to be consistent with constraints from inventories and in situ CO2 datasets. The techniques are applicable in both short-term forecasts and retrospective simulations, thus taking advantage of the coverage and short latency of satellite data while reproducing the major features of long-term inventory and in situ records. Our approach begins with a standard collection of diagnostic fluxes which incorporate a variety of remote-sensing driver data, viz. vegetation indices, fire radiative power, and nighttime lights. We then apply an empirical sink so that global budgets of the diagnostic fluxes match given atmospheric and oceanic growth rates for each year. This step removes coherent, systematic flux errors that produce biases in CO2 which mask the signals an assimilation system hopes to capture. Depending on the simulation mode, the empirical sink uses different choices of atmospheric growth rates: estimates based on observations in retrospective mode and projections based on seasonal forecasts of sea surface temperature in forecasting mode. The retrospective fluxes, when used in simulations with NASA's Goddard Earth Observing System (GEOS), reproduce marine boundary layer measurements with comparable skill to those using fluxes from a modern inversion system. The forecasted fluxes show promising accuracy in their application to the analysis of changes in the carbon cycle as they occur.

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